CO-SPONSORS

RigNet QRI International tessella

Networking Break Sponsor

OSIsoft

Get Involved With The Event

Sponsorship & Exhibition Opportunities Are Limited


Contact us on sponsorship@lbcg.com to reserve an exhibition booth and/or discuss how you can present a white paper case study in one of these areas

  • IoT Technology
  • Industrial IoT Solutions for Oil & Gas
  • Digital Transformation Solutions
  • Digital Oilfield Technology
  • Cloud Platforms
  • Machine Learning Technologies & Applications
  • Machine Learning Training Services
  • Cloud-Based Machine Learning Software
  • Workflow Management Solutions
  • Plug-and-Play Platform
  • AI Software for Oil & Gas
  • AI Technology for  Oil & Gas
  • Augmented Reality (AR) Applications
  • Data Science & Analytics
  • Predictive Analytics
  • Data Extraction
  • Data Protection
  • Network Security
  • Communications Management
  • Edge Devices/Gateways

Meet, Network With & Learn From Senior Business Decision Makers & Technical Infleuncers


Including CEOs, VPs, Heads, Directors, Managers, Team Leads, Chiefs, Managers, Supervisors, Engineers, Scientists, Administrators, Architects of...

  • Data
  • IT
  • IoT
  • Machine Learning
  • Innovation
  • Technology
  • Automation
  • Research & Development
  • Digital Transformation
  • Business Solutions
  • Operational Excellence
  • Corporate Development
  • Plus Technical Titles Including:
  • Production
  • Operations
  • Drilling
  • Completions
  • Exploration
  • Reservoir

E&P DRIVEN SPEAKER LINE-UP LED BY

Alexander Klebanov

Alexander Klebanov

Data Scientist

Chesapeake Energy

David Fulford

David Fulford

Senior Staff Reservoir Engineer

Apache Corporation

Sarita Salunke

Sarita Salunke

Petrophysicist/Data Scientist

BP America 

Christina Bernet

Christina Bernet

Sr. Reservoir Development Engineer

Bonanza Creek Energy

Yuxing Ben

Yuxing Ben

Staff Data Scientist

Anadarko Petroleum 

Graeme Gordon

Graeme Gordon

Sr. Geological Advisor

Hess

Clayton Burrows

Clayton Burrows

Reservoir Engineer - Competitive Intelligence & Operations Support

Apache Corporation

Colleen Graham

Colleen Graham

Data Science Program Manager GOM

Chevron

Ryan Stalker

Ryan Stalker

Change Management & Organizational Development Specialist

Williams

Danny Durham

Danny Durham

Director Global Upstream Chemicals

Apache Corporation

Luis Zorilla

Luis Zorilla

Staff Electrical Engineer

ConocoPhillips

Bill Fairhurst

Bill Fairhurst

President

Riverford Exploration, LLC

Cindy Crow

Cindy Crow

Global Industry Principal

OSIsoft

Dr. Nansen G. Saleri

Dr. Nansen G. Saleri

Chairman, CEO, Co-Founder

Quantum Reservoir Impact (QRI)

Maximizing Productivity, Enhance Efficiency, Boost Revenue & Increase Safety

MACHINE LEARNING & AI FOR UPSTREAM ONSHORE OIL & GAS 2019

Digital transformations are predicted to transform the economics of upstream operations by reducing expenditures, improving maintenance efficiency, and providing a granular view of workflows, enabling more effective decision-making.  At the heart of all these digitisation efforts...lies machine learning.

Machine learning and AI applications could save the oil and gas industry as much as $50 billion in the coming decade, according to McKinsey.  Since the global oil price re-set in late 2014, companies have increasingly been looking at technology to reduce costs, improve efficiency and minimize downtime but there is still a lack of understanding of what value AI can actually create for the industry, and what cost and operational benefits it can bring.

DESIGNED TO DELIVER SOLUTIONS FOR UPSTREAM ONSHORE OPERATORS

Operators, large, medium or small, are continually looking for ways to improve operational efficiency, make operations faster and more efficient, make assets run better, find bottlenecks in processes, find asset failures before they occur, eliminate unplanned downtime. What they are beginning to realize is that there are ways to improve every single one of those metrics using Machine Learning and AI.

The recent influx of AI technologies means the opportunity to process numerous real-time data sets, every minute of every day, and build models where you are able to quantity change and achieve even greater cost savings in the short term, all operational areas, is now within reach.  Production optimization is definitely where the real advantage is to solve engineering problems with Machine Learning and AI.

With this mind, the Machine Learning & AI For Upstream Onshore Oil & Gas 2019 purely focuses on understanding the profitable applications of Machine Learning and AI, primarily for optimizing production for onshore E&Ps, and examine how to improve operational efficiencies in drilling and completions.

Day 1 - Business Cases And Examples On:

  • Justifying Investment In Machine Learning & AI
  • Learn Where Machine Learning & AI Delivers The Greatest Value
  • Case Studies Of Successful Outcomes From Machine Learning In Oil & Gas Operations With An Emphasis On Tying ROI Back To Your Business Objectives

Day 2 - Deep-Dive Into The Technology

  • Create A Technology Road Map For The Short-Term In Line With Business Objectives
  • Optimize Maintenance Processes And Eliminate Down Time
  • Overcome The Full Horizon Of Data Science Challenges
Download Speaker Interviews

Agenda At A Glance

Machine Learning & AI For Upstream Onshore Oil & Gas 2019

  • How To Utilize The Latest Machine Learning Technology To Save Costs And Improve Efficiency
  • Bottom Line Benefits And Current Innovations
  • Operational Understanding Of The Black Box Nature of AI
  • Machine Learning Value - Permian Basin Operator Case Study
  • Subsurface Optimization Case Study
  • Completions And Well Spacing Case Study
  • Cycle-Time For Artificial Lifts Case Study
  • Predictive Maintenance For Artificial Lifts Case Study
  • Ensuring Asset Reliability
  • Predictive Maintenance Strategies
  • Predict Anomalies On Artificial Lift Equipment To Pre-Empt Failure
  • Ensuring Asset Reliability    
  • Predictive Maintenance Strategies    
  • Collecting, Using & Profiting From The Data Upgrading Legacy Infrastructure Systems    
  • Machine Models
  • Improving Well Design Decisions
  • Skills Transformation Within The Organization    
  • Change Management

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